Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add DMDuFresne/questllens --skill questllens-health-checkgit clone --depth 1 https://github.com/DMDuFresne/questllensWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dmdufresne/questllens/questllens-health-check)<a href="https://agentmods.dev/skills/dmdufresne/questllens/questllens-health-check"><img src="https://agentmods.dev/badge/skills/dmdufresne/questllens/questllens-health-check/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dmdufresne/questllens/questllens-health-check"><img src="https://agentmods.dev/badge/skills/dmdufresne/questllens/questllens-health-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00102 | $0.00987 |
| Opus 5.5 | $0.00041 | $0.00395 |
| Sonnet 5.5 | $0.00020 | $0.00197 |
| Haiku 4.5 | $0.00010 | $0.00099 |
Grade A, and why
questllens-health-check scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
questllens-health-check
Triage order. Each step is cheap and rules out a class of problem, so run them in sequence rather than jumping to the one that matches your hunch.
1. Ingestion first — it explains most "missing data"
get_ingestion_health is the single highest-value call. One round trip gives you, per
table: WAL lag, suspended state, the latest designated-timestamp value, and staleness against
wall clock — sorted suspended-first, then by lag.
Read it in this order:
- Suspended tables. A suspended WAL means writes are accepted but never applied. Queries return stale data with no error anywhere. This is the top-priority finding and it is invisible from the query path alone.
- High lag. Apply is behind. Data is arriving but not yet visible. Often transient under load; sustained lag is a real problem.
- Staleness with zero lag. WAL is healthy and caught up, and the newest row is still old — so nothing is writing. The problem is upstream of QuestDB, not inside it.
That last distinction matters more than any other in this skill: lag is a database problem, staleness without lag is a producer problem. Don't report "ingestion is broken" without saying which.
get_wal_status drills into WAL apply state, per-table lag, and sequencer vs writer
transaction numbers when you need the detail behind a finding.
2. Is anything actually running
get_running_queries — optionally with min_duration_ms to filter noise. A long-running
query can starve apply and make lag look like a data problem.
questllens cannot cancel a query. Report what's running, its duration, and the impact; the operator decides.
3. Storage and layout
get_storage_summarywithtop_n— largest tables, native vs parquet. Run this before anyone asks "why is the disk full".get_partitionswithsummary=true— roll-up totals per table; dropsummaryand usefrom/toto inspect a suspicious window. Look for: a missing partition (ingestion gap), a partition far larger than its neighbours (backfill or out-of-order write storm), or a partition count that doesn't match the retention the operator expects.get_table_params—ttltells you whether retention is configured at all;o3MaxLagandmaxUncommittedRowsgovern how expensive out-of-order writes are.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 78 lines · 102 tokens per session scan A ec4233fe86f5
questllens-health-check is a skill published in the GitHub repository DMDuFresne/questllens (0 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 102 tokens to every session and 987 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
questllens-health-check compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| questllens-health-checkDMDuFresne/questllens | Skill | 0 | 2mo ago | Apache-2.0 | A | 102 | Claude Code, Codex |
| reproduce-buggoogleapis/mcp-toolbox | Skill | 17k | yesterday | Apache-2.0 | A | 130 | Claude Code, Codex |
| triage-issuesgoogleapis/mcp-toolbox | Skill | 17k | yesterday | Apache-2.0 | A | 164 | Claude Code, Codex |
| postgresql-indexingprowler-cloud/prowler | Skill | 15k | yesterday | Apache-2.0 | A | 108 | Claude Code |
| graphjin-evaldosco/graphjin | Skill | 3.2k | yesterday | Apache-2.0 | A | 27 | Claude Code, Codex |
| axiom-audit-grdb-performanceCharlesWiltgen/Axiom | Skill | 1.3k | 2d ago | MIT | A | 43 | Codex |
| django-perf-reviewgetsentry/skills | Skill | 1.1k | 2d ago | Apache-2.0 | A | 55 | Claude Code |